Data Center Infrastructure Architect

Compensation

$360K – $530K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts
• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)
• 401(k) retirement plan with employer match
• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)
• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees
• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)
• Mental health and wellness support
• Employer-paid basic life and disability coverage
• Annual learning and development stipend to fuel your professional growth
• Daily meals in our offices, and meal delivery credits as eligible
• Relocation support for eligible employees
• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

About the Team

OpenAI’s Industrial Compute team is building and productizing infrastructure capabilities that help organizations deploy and operate advanced AI systems at scale. The team works across AI hardware, systems engineering, physical infrastructure, and customer delivery to turn emerging technologies into reliable, repeatable infrastructure solutions.

About the Role

We are seeking a senior, hands-on Data Center Infrastructure Architect to develop and optimize the physical infrastructure required for large-scale AI deployments.

This is a broad technical role spanning data center architecture, electrical and mechanical systems, high-density compute, controls, telemetry, and digital modeling. You will use simulation, operational data, and digital-twin approaches to evaluate infrastructure designs, identify system-level constraints, and improve efficiency, reliability, cost, and speed of deployment.

The ideal candidate can move fluidly between first-principles analysis, facility and equipment design, computational modeling, engineering review, and real-world implementation. You should be comfortable working across disciplines rather than operating solely within electrical, mechanical, or software boundaries.

Key Responsibilities

• Define system-level architectures for high-density AI data centers across power, cooling, IT equipment, controls, and facility infrastructure.
• Develop digital twins and other computational models that represent the behavior of data center systems under changing workloads, environmental conditions, equipment configurations, and failure scenarios.
• Use design and operational data to identify constraints, improve PUE and related efficiency metrics, and optimize capacity, reliability, water consumption, cost, and deployment schedules.
• Evaluate tradeoffs across electrical topology, cooling architecture, rack density, redundancy, controls, maintainability, constructability, and operational complexity.
• Translate evolving AI hardware requirements into practical facility, rack, power, and thermal architectures.
• Establish reference architectures, modeling standards, design assumptions, performance requirements, and validation methodologies that can be reused across customer deployments.
• Partner with software, data, controls, hardware, mechanical, electrical, construction, commissioning, and operations teams to connect digital models with real infrastructure behavior.
• Integrate telemetry from systems such as BMS, EPMS, DCIM, SCADA, equipment controllers, and IT hardware into modeling and optimization workflows.
• Lead technical reviews of customer and partner designs, identify material risks, and recommend changes grounded in quantitative analysis.
• Work with customers and delivery teams to adapt reference solutions to site-specific constraints while preserving performance, reliability, and efficiency objectives.
• Support pilots, commissioning, performance testing, and post-deployment analysis to validate models and continuously improve infrastructure designs.
• Help shape the technical roadmap for Industrial Compute’s physical-infrastructure products and engineering services.

Qualifications

• Significant experience designing or optimizing hyperscale data centers, large mission-critical facilities, or comparable infrastructure systems.
• Broad knowledge of data center electrical and mechanical systems, including power distribution, backup power, thermal management, liquid cooling, heat rejection, controls, and monitoring.
• Experience making system-level design decisions across multiple engineering disciplines.
• Experience developing or applying simulation, optimization, digital-twin, or physics-based modeling techniques to physical infrastructure.
• Strong understanding of data center efficiency and performance metrics, including PUE, WUE, utilization, capacity, reliability, and total cost of ownership.
• Experience working with operational telemetry and translating real-world system behavior into design improvements.
• Ability to evaluate complex tradeoffs involving performance, reliability, cost, schedule, scalability, sustainability, and maintainability.
• Demonstrated ability to lead technical work in ambiguous, rapidly changing environments.
• Strong written and verbal communication skills, including the ability to explain complex engineering decisions to customers, executives, and cross-functional teams.
• Bachelor’s degree in mechanical engineering, electrical engineering, systems engineering, applied physics, or a related technical discipline.

Preferred Skills

• Experience with high-density GPU clusters and direct-to-chip liquid cooling.
• Experience connecting facility models with workload, rack, server, or chip-level power and thermal behavior.
• Familiarity with modeling or engineering tools such as Modelica, MATLAB/Simulink, Python, EnergyPlus, computational fluid dynamics tools, or equivalent platforms.
• Experience with BMS, EPMS, DCIM, SCADA, PLCs, data historians, or industrial controls.
• Experience developing reference designs or new infrastructure architectures within a hyperscaler, data center operator, advanced engineering organization, or major design consultancy.
• Experience taking an infrastructure concept from modeling and prototype validation through deployment and operational feedback.
• Advanced degree in an engineering or scientific discipline.

Success in the First Year

• Establish a credible system-level model of power, cooling, compute, and facility behavior for priority Industrial Compute use cases.
• Identify and validate meaningful opportunities to improve efficiency, capacity, reliability, or deployment cost.
• Deliver reusable reference architectures and engineering methodologies for customer deployments.
• Create a repeatable feedback loop connecting modeling, operational telemetry, commissioning results, and future design decisions.
• Become a trusted technical partner to internal engineering teams, customers, and infrastructure delivery partners.